Adjustment of analgesic stimulation parameters based on trust dynamic measurements

ABSTRACT

Systems and techniques are disclosed to establish programming of an implantable electrical neurostimulation device for treating pain of a human subject, through the use and adjustment of analgesic stimulation parameters based on trust dynamics and trust measurements. In an example, the system to establish programming of the neurostimulation device performs operations that: determine a trust measurement value that is derived from results of at least one commitment made with a human subject, via observable interactions; determine a modification of at least one neurostimulation programming parameter, based on the trust measurement value; and to cause the implantable neurostimulation device to implement the modification of the at least one neurostimulation programming parameter. Further examples are provided to produce and track the trust measurement value, as well as identify a pain susceptibility value and determine a receptiveness to analgesic effects based on these and other trust dynamics.

CLAIM OF PRIORITY

This application claims the benefit of priority under 35 U.S.C. § 119(e)of U.S. Provisional Patent Application Ser. No. 62/675,000, filed on May22, 2018, and titled “ADJUSTMENT OF ANALGESIC STIMULATION PARAMETERSBASED ON TRUST DYNAMIC MEASUREMENTS”, which is incorporated by referenceherein in its entirety.

DISCLAIMER

The claims and scope of the subject application, and any continuation,divisional or continuation-in-part applications claiming priority to thesubject application, are solely limited to embodiments (e.g., systems,apparatus, methodologies, computer program products and computerreadable storage media) directed to implanted electrical stimulation forpain treatment and/or management.

STATEMENT REGARDING JOINT RESEARCH AND DEVELOPMENT

The present subject matter was developed and the claimed invention wasmade by or on behalf of Boston Scientific Neuromodulation Corporationand International Business Machines Corporation, parties to a jointresearch agreement that was in effect on or before the effective filingdate of the claimed invention, and the claimed invention was made as aresult of activities undertaken within the scope of the joint researchagreement.

TECHNICAL FIELD

The present disclosure relates generally to medical devices, and moreparticularly, to systems, devices, and methods for electricalstimulation programming techniques, to perform implanted electricalstimulation for pain treatment and/or management.

BACKGROUND

Neurostimulation, also referred to as neuromodulation, has been proposedas a therapy for a number of conditions. Examples of neurostimulationinclude Spinal Cord Stimulation (SCS), Deep Brain Stimulation (DBS),Peripheral Nerve Stimulation (PNS), and Functional ElectricalStimulation (FES). Implantable neurostimulation systems have beenapplied to deliver such a therapy. An implantable neurostimulationsystem may include an implantable neurostimulator, also referred to asan implantable pulse generator (IPG), and one or more implantable leadseach including one or more electrodes. The implantable neurostimulatordelivers neurostimulation energy through one or more electrodes placedon or near a target site in the nervous system.

A neuromodulation system can be used to electrically stimulate tissue ornerve centers to treat nervous or muscular disorders. For example, anSCS system may be configured to deliver electrical pulses to a specifiedregion of a patient's spinal cord, such as particular spinal nerve rootsor nerve bundles, to create an analgesic effect that masks painsensation. While modern electronics can accommodate the need forgenerating and delivering stimulation energy in a variety of forms, thecapability of a neurostimulation system depends on itspost-manufacturing programmability to a great extent. For example, asophisticated neurostimulation program may only benefit a patient whenit is customized for that patient, and stimulation patterns or programsof patterns that are predetermined at the time of manufacturing maysubstantially limit the potential for the customization.

SUMMARY

The following Summary provides examples as an overview of some of theteachings of the present application and not intended to be an exclusiveor exhaustive treatment of the present subject matter. Further detailsabout the present subject matter are found in the detailed descriptionand appended claims. Other aspects of the disclosure will be apparent topersons skilled in the art upon reading and understanding the followingdetailed description and viewing the drawings that form a part thereof,each of which are not to be taken in a limiting sense. The scope of thepresent disclosure is defined by the appended claims and their legalequivalents.

Example 1 is a system for use to adjust programming of an implantableelectrical neurostimulation device for treating pain, the systemcomprising: at least one processor; and at least one memory devicecomprising instructions, which when executed by the processor, cause theprocessor to perform operations that: determine a trust measurementvalue, the trust measurement value being derived from results of atleast one commitment made with a human subject, and the at least onecommitment being associated with a plurality of interactions with thehuman subject; determine a modification of at least one neurostimulationprogramming parameter of the implantable neurostimulation device, basedon the trust measurement value; and provide instructions to cause theimplantable neurostimulation device to implement the modification of theat least one neurostimulation programming parameter.

In Example 2, the subject matter of Example 1 includes, the trustmeasurement value being further derived from a reaction of the humansubject to a fulfillment or a violation of the at least one commitment,and wherein the trust measurement value is determined with a classifierthat performs analysis of the plurality of interactions for thefulfillment or the violation of the at least one commitment, theclassifier being trained to predict a trust disposition for the humansubject towards an other entity during the plurality of interactions.

In Example 3, the subject matter of Example 2 includes, an amount of themodification of the at least one neurostimulation programming parameterfrom a first state to a second state being correlated to an amount ofchange in the trust measurement value from a first state to a secondstate.

In Example 4, the subject matter of Examples 2-3 includes, the pluralityof interactions being performed with text or voice conversationsoccurring between the human subject and the other entity, wherein theother entity creates the commitment with the human subject and performsat least one observable action to cause the fulfillment or the violationof the at least one commitment.

In Example 5, the subject matter of Example 4 includes, the trustmeasurement value being representable as a value within a trust graph,wherein the trust graph provides a measurement of trust between thehuman subject and the other entity, based on evaluation of the humansubject with the plurality of interactions over a period of time.

In Example 6, the subject matter of Examples 2-5 includes, furtheroperations that: identify a pain susceptibility value applicable to thehuman subject, based on the trust measurement value derived from the atleast one commitment; wherein the pain susceptibility value is based atleast in part on a prediction of the trust disposition for the humansubject towards the other entity; and wherein the modification of atleast one neurostimulation programming parameter of the implantableneurostimulation device, is further based on the pain susceptibilityvalue.

In Example 7, the subject matter of Example 6 includes, the operationsto identify the pain susceptibility value for the human subject beingfurther based on an identification of a pain measurement value derivedfrom a neuroimaging procedure performed on the human subject.

In Example 8, the subject matter of Example 7 includes, theidentification of the pain measurement value being derived from theneuroimaging procedure is used to determine a baseline to predict aplacebo response of modification of the at least one neurostimulationprogramming parameter.

In Example 9, the subject matter of Examples 1-8 includes, the resultsof at least one commitment being determined from an observation of areaction of the human subject to a violation or fulfillment of the atleast one commitment, and wherein the observation of the reaction isdetermined from the plurality of interactions with the human subject.

In Example 10, the subject matter of Examples 1-9 includes, furtheroperations that: determine a subsequent trust measurement metric, thesubsequent trust measurement metric being determined from a series ofinteractions with the human subject conducted after the modification ofthe at least one neurostimulation programming parameter; determine asubsequent modification of the at least one neurostimulation programmingparameter of the implantable neurostimulation device, based on thesubsequent trust measurement metric; and provide instructions to causethe implantable neurostimulation device to implement the subsequentmodification of the at least one neurostimulation programming parameter.

In Example 11, the subject matter of Examples 1-10 includes, themodification of the at least one neurostimulation programming parametercausing a change for one or more of: pulse patterns, pulse shapes, aspatial location of pulses, waveform shapes, or a spatial location ofwaveform shapes, for modulated energy provided with a plurality of leadsof the implantable neurostimulation device.

In Example 12, the subject matter of Examples 1-11 includes, themodification of the at least one neurostimulation programming parameterbeing provided in a neurostimulation program for the implantableneurostimulation device, with further operations to update theneurostimulation program based on the modification of the at least oneneurostimulation programming parameter.

In Example 13, the subject matter of Examples 1-12 includes, theimplantable neurostimulation device being further configured to treatpain by delivering at least one of: an electrical spinal cordstimulation, an electrical brain stimulation, or an electricalperipheral nerve stimulation, in the human subject.

Example 14 is a machine-readable medium including instructions, whichwhen executed by a machine, cause the machine to perform the operationsof the system of any of the Examples 1 to 13.

Example 15 is a method to perform the operations of the system of any ofthe Examples 1 to 13.

Example 16 is a device for use to adjust programming of an implantableelectrical neurostimulation device for treating pain, the devicecomprising: at least one processor and at least one memory; datameasurement processing circuitry, operable with the processor and thememory, the data measurement processing circuitry configured todetermine a trust measurement value from results of at least onecommitment made with a human subject, with the at least one commitmentbeing associated with a plurality of interactions with the humansubject; neurostimulation programming circuitry, in operation with theat least one processor and the at least one memory, configured to:determine a modification of at least one neurostimulation programmingparameter of the implantable neurostimulation device, based on the trustmeasurement value; and provide instructions to cause the implantableneurostimulation device to implement the modification of the at leastone neurostimulation programming parameter.

In Example 17, the subject matter of Example 16 includes, the datameasurement processing circuitry further configured to: determine thetrust measurement value from a reaction of the human subject to afulfillment or a violation of the at least one commitment; wherein thetrust measurement value is determined with a classifier that performsanalysis of the plurality of interactions for the fulfillment or theviolation of the at least one commitment, and wherein the classifier istrained to predict a trust disposition for the human subject towards another entity during the plurality of interactions.

In Example 18, the subject matter of Example 17 includes, an amount ofthe modification of the at least one neurostimulation programmingparameter from a first state to a second state being correlated to anamount of change in the trust measurement value from a first state to asecond state.

In Example 19, the subject matter of Examples 17-18 includes, theplurality of interactions being performed with text or voiceconversations occurring between the human subject and the other entity,wherein the other entity creates the commitment with the human subjectand performs at least one observable action to cause the fulfillment orthe violation of the at least one commitment.

In Example 20, the subject matter of Examples 17-19 includes, the trustmeasurement value being representable as a value within a trust graph,wherein the trust graph provides a measurement of trust between thehuman subject and the other entity, based on evaluation of the humansubject with the plurality of interactions over a period of time.

In Example 21, the subject matter of Examples 17-20 includes, the datameasurement processing circuitry further configured to: identify a painsusceptibility value applicable to the human subject, based on the trustmeasurement value derived from the at least one commitment; wherein thepain susceptibility value is based at least in part on a prediction ofthe trust disposition for the human subject towards the other entity;and wherein the modification of at least one neurostimulationprogramming parameter of the implantable neurostimulation device, isfurther based on the pain susceptibility value.

In Example 22, the subject matter of Example 21 includes, the operationsto identify the pain susceptibility value for the human subject beingfurther based on an identification of a pain measurement value derivedfrom a neuroimaging procedure performed on the human subject; andwherein the identification of the pain measurement value derived fromthe neuroimaging procedure is used to determine a baseline to predict aplacebo response of modification of the at least one neurostimulationprogramming parameter.

In Example 23, the subject matter of Examples 16-22 includes, theresults of at least one commitment being determined from an observationof a reaction of the human subject to a violation or fulfillment of theat least one commitment, and wherein the observation of the reaction isdetermined from the plurality of interactions with the human subject.

In Example 24, the subject matter of Examples 16-23 includes, the datameasurement processing circuitry further configured to: determine asubsequent trust measurement metric, the subsequent trust measurementmetric being determined from a series of interactions with the humansubject conducted after the modification of the at least oneneurostimulation programming parameter; determine a subsequentmodification of the at least one neurostimulation programming parameterof the implantable neurostimulation device, based on the subsequenttrust measurement metric; and provide instructions to cause theimplantable neurostimulation device to implement the subsequentmodification of the at least one neurostimulation programming parameter.

In Example 25, the subject matter of Examples 16-24 includes, themodification of the at least one neurostimulation programming parameterbeing provided in a neurostimulation program for the implantableneurostimulation device, wherein the neurostimulation programmingcircuitry is further configured to: update the neurostimulation programbased on the modification of the at least one neurostimulationprogramming parameter; wherein the modification of the at least oneneurostimulation programming parameter causes a change for one or moreof: pulse patterns, pulse shapes, a spatial location of pulses, waveformshapes, or a spatial location of waveform shapes, for modulated energyprovided with a plurality of leads of the implantable neurostimulationdevice.

Example 26 is a method for use to adjust programming of an implantableelectrical neurostimulation device for treating pain, the methodcomprising a plurality of operations executed with at least oneprocessor of an electronic device, the plurality of operationscomprising: identifying a trust measurement value, the trust measurementvalue being derived from results of at least one commitment made with ahuman subject, and the at least one commitment being associated with aplurality of interactions with the human subject; determining amodification of at least one neurostimulation programming parameter ofthe implantable neurostimulation device, based on the trust measurementvalue; and causing the implantable neurostimulation device to implementthe modification of the at least one neurostimulation programmingparameter.

In Example 27, the subject matter of Example 26 includes: determiningthe trust measurement value from a reaction of the human subject to afulfillment or a violation of the at least one commitment; wherein thetrust measurement value is determined with a classifier that performsanalysis of the plurality of interactions for the fulfillment or theviolation of the at least one commitment, and wherein the classifier istrained to predict a trust disposition for the human subject towards another entity during the plurality of interactions.

In Example 28, the subject matter of Example 27 includes, an amount ofthe modification of the at least one neurostimulation programmingparameter from a first state to a second state being correlated to anamount of change in the trust measurement value from a first state to asecond state.

In Example 29, the subject matter of Examples 27-28 includes, theplurality of interactions being performed with text or voiceconversations occurring between the human subject and the other entity,wherein the other entity creates the commitment with the human subjectand performs at least one observable action to cause the fulfillment orthe violation of the at least one commitment.

In Example 30, the subject matter of Examples 27-29 includes, the trustmeasurement value being representable as a value within a trust graph,and wherein the trust graph provides a measurement of trust between thehuman subject and the other entity, based on evaluation of the humansubject with the plurality of interactions over a period of time.

In Example 31, the subject matter of Examples 27-30 includes:identifying a pain susceptibility value applicable to the human subject,based on the trust measurement value derived from the at least onecommitment; wherein the pain susceptibility value is based at least inpart on a prediction of the trust disposition for the human subjecttowards the other entity; and wherein the modification of at least oneneurostimulation programming parameter of the implantableneurostimulation device, is further based on the pain susceptibilityvalue.

In Example 32, the subject matter of Example 31 includes, whereinidentifying the pain susceptibility value for the human subject isfurther based on an identification of a pain measurement value derivedfrom a neuroimaging procedure performed on the human subject; andwherein the identification of the pain measurement value derived fromthe neuroimaging procedure is used to determine a baseline to predict aplacebo response of modification of the at least one neurostimulationprogramming parameter.

In Example 33, the subject matter of Examples 26-32 includes, theresults of at least one commitment being determined from an observationof a reaction of the human subject to a violation or fulfillment of theat least one commitment, wherein the observation of the reaction isdetermined from the plurality of interactions with the human subject.

In Example 34, the subject matter of Examples 26-33 includes:identifying a subsequent trust measurement metric, the subsequent trustmeasurement metric being identified from a series of interactions withthe human subject conducted after the modification of the at least oneneurostimulation programming parameter; determining a subsequentmodification of the at least one neurostimulation programming parameterof the implantable neurostimulation device, based on the subsequenttrust measurement metric; and causing the implantable neurostimulationdevice to implement the subsequent modification of the at least oneneurostimulation programming parameter.

In Example 35, the subject matter of Examples 26-34 includes, themodification of the at least one neurostimulation programming parameterbeing provided in a neurostimulation program for the implantableneurostimulation device, with the operations further comprising:updating the neurostimulation program based on the modification of theat least one neurostimulation programming parameter; wherein themodification of the at least one neurostimulation programming parametercauses a change for one or more of: pulse patterns, pulse shapes, aspatial location of pulses, waveform shapes, or a spatial location ofwaveform shapes, for modulated energy provided with a plurality of leadsof the implantable neurostimulation device.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments are illustrated by way of example in the figures ofthe accompanying drawings. Such embodiments are demonstrative and notintended to be exhaustive or exclusive embodiments of the presentsubject matter.

FIG. 1 illustrates, by way of example, an embodiment of aneurostimulation system.

FIG. 2 illustrates, by way of example, an embodiment of a stimulationdevice and a lead system, such as may be implemented in theneurostimulation system of FIG. 1.

FIG. 3 illustrates, by way of example, an embodiment of a programmingdevice, such as may be implemented in the neurostimulation system ofFIG. 1.

FIG. 4 illustrates, by way of example, an implantable neurostimulationsystem and portions of an environment in which the system may be used.

FIG. 5 illustrates, by way of example, an embodiment of an implantablestimulator and one or more leads of a neurostimulation system, such asthe implantable neurostimulation system of FIG. 4.

FIG. 6 illustrates, by way of example, an embodiment of a patientprogramming device for a neurostimulation system, such as theimplantable neurostimulation system of FIG. 4.

FIG. 7 illustrates, by way of example, an embodiment of datainteractions among a programming device, a program modeling system, apatient interaction computing device, and a data service for selectingand implementing respective analgesic parameter settings for operationof a neurostimulation device based on trust dynamics.

FIG. 8 illustrates, by way of example, an embodiment of functionalcomponents and data sets used in selecting and implementing respectiveanalgesic parameter settings for operation of a neurostimulation devicebased on trust dynamics.

FIG. 9 illustrates, by way of example, an embodiment of a data andcontrol flow between trust determination and neurostimulation programmodeling operations, used in selecting and implementing respectiveanalgesic parameter settings for operation of a neurostimulation devicebased on trust dynamics.

FIG. 10 illustrates, by way of example, an embodiment of a processingmethod implemented by a system or device for use to adjust programmingof an implantable electrical neurostimulation device based on trustdynamics.

FIG. 11 illustrates, by way of example, a block diagram of an embodimentof a computing system implementing data measurement determinationcircuitry for use to adjust programming of an implantable electricalneurostimulation device for treating pain of a human subject.

FIG. 12 illustrates, by way of example, a block diagram of an embodimentof a computing system implementing neurostimulation programmingcircuitry for use to establish programming of an implantable electricalneurostimulation device for treating pain of a human subject.

FIG. 13 is a block diagram illustrating a machine in the example form ofa computer system, within which a set or sequence of instructions may beexecuted to cause the machine to perform any one of the methodologiesdiscussed herein, according to an example embodiment.

DETAILED DESCRIPTION

This document discusses various techniques that can generate programmingof an implantable electrical neurostimulation device, for the treatmentof pain of a human subject (e.g., a patient). As an example, varioussystems and methods are described to adjust analgesic stimulationparameters of neurostimulation treatment based on a measure of trustdynamics. These systems and methods are designed to exploit a measure oftrust disposition in a subject patient to deliver or modifyneurostimulation treatment that is associated with an expected painresponse. Specifically, the relationship between trust and pain (and apatient's response to pain treatments) is exploited so that suitableadjustments can be made to the amount, type, and characteristics ofneurostimulation treatment that cause analgesic (e.g., pain-decreasing,masking) effects in a patient.

Chronic pain is a common condition for many patients, but a conditionwhich may be addressed through the use of neurostimulation therapy(e.g., electrical spinal cord stimulation, electrical peripheral nervestimulation, or electrical brain stimulation) to deliver treatment. Onelimiting factor for existing applications of neurostimulation therapiesis that, even if a number of advanced programs can be applied by aneurostimulation device, patients often only end up using very few ofthe available treatments (e.g., two or three programs) suggested by aclinician or other medical professional. As a result, the treatmentresults are often not effective and the patient ends up applyingprograms that are not customized to the patient or a best fit for thepatient's current state. The present techniques and systems improve thisscenario through the use of a program modeling system adaptive to thetrust state of the patient. This program modeling system is able tomodify neurostimulation programs and program parameters that areappropriate for a patient based on the patient's state of pain, thepatient's susceptibility to pain, the patient's likelihood of respondingto pain treatment, and other characteristics that are derivable or tiedto trust measurements and trust disposition. These trust measurementsand trust disposition are in turn determined by the observation ormeasurement of interactions and commitments made in such interactions.As a result, a scientific and objective way of measuring and predictingtrust in a patient can lead to new types of neurostimulation treatmentsand treatment results.

The program modeling system discussed herein enables the adaptation ofneurostimulation parameters based on multiple aspects of painmeasurements, including pain susceptibility, treatment susceptibility,predicted treatment effectiveness, and patient feedback, all tied totrust measures or trust predictions. The program modeling systemprovides a dynamic system that is responsive to the unique trust stateof patient, which in turn is tied to the susceptibility of the patientto experience pain and/or respond to pain treatments. In an example, theprogram modeling system generates a modification of a neurostimulationprogramming parameter directly based on a trust measurement value. Inother examples, the program modeling system converts the trustmeasurement value into a pain susceptibility value, and generates themodification of the neurostimulation programming parameter directlybased on the pain susceptibility value. Other indirect measurements andevaluations of pain, trust, and treatment effectiveness may also beincorporated into the program modeling system.

The stimulator input produced by the program modeling system enablesexploration of a set of possible neurostimulation programs and programsettings that are expanded and adapted over time, as parameters arecreated, modified, or selected for the particular patient. Theseprogramming parameters may be arranged or defined (e.g., created,modified, activated, etc.) into new or updated sets of neurostimulationoperational programs (also plainly referred to as “programs” in thisdocument), resulting in an identification of a particularneurostimulation program that includes at least a portion of the paintreatment parameters identified as a best-fit for the human patient,given a particular state of trust, state of pain, and treatmentobjectives. The deployment and programming of these parameters andprogram(s) may be provided and monitored, with further feedback beingcollected on how successful a particular treatment is relative to thestate of pain and the state of trust by the patient.

The trust modeling system disclosed herein employs a dynamical model tocompute trust values based on an assessment of patient interactions withanother human or automated entity. These interactions are observed asconditions are established, fulfilled, modified, and violated. Theseinteractions may be simple or complex in nature (e.g., involving asimple promise made and immediately fulfilled by an agent, or a complexset of conditions and actions between multiple parties), and may occurin a variety of automated agent-based settings (e.g., with a chat bot orpersonal digital assistant) or human-based settings (e.g., discussionbetween two people, such as the patient and a clinician, nurse, or otheragent). The state of trust of a patient may be determined in variousexamples with use of a trust classifier, including a classifier orclassification model adapted from various forms of artificialintelligence, machine learning, or data structures. The state of trustor trust measurements of a patient also may be represented in a trustgraph, neural network, or other advanced data structure. This classifierand trust graph may be trained over time to generate an ongoingprediction of trust values from future communication with the chatbot orothers.

The techniques of this document enable automatic or human-drivenimprovements that create, establish, activate, select, modify, update,or adapt programming for a neurostimulation device (or to re-program aneurostimulation device) based on trust dynamics. These techniquesaccordingly improve pain treatment techniques and treatment efficacy ofneurostimulation device usage, based on the particular physiological(and mental and emotional) state of a patient and the patient'sreceptiveness for treatment. Given the large number of permutations inneurostimulation output available in any given program, and the widevariation among different types of programs, such customization ofneurostimulation parameters to a particular patient's pain state or painsusceptibility is not feasible with many existing approaches.

In an example, a parameter adjustment is initiated by the trust modelingsystem and program modeling system to dynamically select, adjust, andmodify neurostimulation treatment that provides an analgesic effectcorrelated to pain and treatment states of a human subject. Theprogramming selection, adjustment, and modification logic of the programmodeling system operates to identify appropriate neurostimulationprogramming parameters using the previously described trust model, andidentify values of the programming parameters that predict animprovement to pain treatment and a state of pain. Finally, theprogramming selection, adjustment, and modification logic of the programmodeling system operates to collect feedback from subsequent conditionsand changes in trust measurements, pain measurements, and susceptibilityto treatment, to provide an ongoing treatment adjustment for thepredicted state of the patient and the patient's chronic pain.

By way of example, operational parameters of the neurostimulation devicemay include amplitude, frequency, duration, pulse width, pulse type,patterns of neurostimulation pulses, waveforms in the patterns ofpulses, and like settings with respect to the intensity, type, andlocation of neurostimulator output on individual or a plurality ofrespective leads. The neurostimulator may use current or voltage sourcesto provide the neurostimulator output, and apply any number of controltechniques to modify the electrical simulation applied to anatomicalsites or systems related to pain or analgesic effect. In variousembodiments, a neurostimulator program may include parameters thatdefine spatial, temporal, and informational characteristics for thedelivery of modulated energy, including the definitions or parameters ofpulses of modulated energy, waveforms of pulses, pulse blocks eachincluding a burst of pulses, pulse trains each including a sequence ofpulse blocks, train groups each including a sequence of pulse trains,and programs of such definitions or parameters, each including one ormore train groups scheduled for delivery. Characteristics of thewaveform that are defined in the program may include, but are notlimited to the following: amplitude, pulse width, frequency, totalcharge injected per unit time, cycling (e.g., on/off time), pulse shape,number of phases, phase order, interphase time, charge balance, ramping,as well as spatial variance (e.g., electrode configuration changes overtime). It will be understood that based on the many characteristics ofthe waveform itself, a program may have many parameter settingcombinations that would be potentially available for use.

In various embodiments, the present subject matter may be implementedusing a combination of hardware and software designed to provide userssuch as patients, caregivers, clinicians, researchers, physicians, orothers with the ability to generate, identify, select, implement, andupdate neurostimulation programs that provide analgesic effect for paintreatment of a human subject. The adaptation of such neurostimulationprograms may result in variation in the location, intensity, and type ofdefined waveforms and patterns in an effort to increase therapeuticefficacy and/or patient satisfaction for neurostimulation therapies,including but not being limited to SCS and DBS therapies. Whileneurostimulation is specifically discussed as an example, the presentsubject matter may apply to any therapy that employs stimulation pulsesof electrical or other forms of energy for treating chronic pain.

The delivery of neurostimulation energy that is discussed herein may bedelivered in the form of electrical neurostimulation pulses. Thedelivery is controlled using stimulation parameters that specify spatial(where to stimulate), temporal (when to stimulate), and informational(patterns of pulses directing the nervous system to respond as desired)aspects of a pattern of neurostimulation pulses. Many currentneurostimulation systems are programmed to deliver periodic pulses withone or a few uniform waveforms continuously or in bursts. However,neural signals may include more sophisticated patterns to communicatevarious types of information, including sensations of pain, pressure,temperature, etc. Accordingly, the following drawings provide anintroduction to the features of an example neurostimulation system andhow such programming may be accomplished through neurostimulationsystems.

FIG. 1 illustrates an embodiment of a neurostimulation system 100.System 100 includes electrodes 106, a stimulation device 104, and aprogramming device 102. Electrodes 106 are configured to be placed on ornear one or more neural targets in a patient. Stimulation device 104 isconfigured to be electrically connected to electrodes 106 and deliverneurostimulation energy, such as in the form of electrical pulses, tothe one or more neural targets though electrodes 106. The delivery ofthe neurostimulation is controlled by using a plurality of stimulationparameters, such as stimulation parameters specifying a pattern of theelectrical pulses and a selection of electrodes through which each ofthe electrical pulses is delivered. In various embodiments, at leastsome parameters of the plurality of stimulation parameters areprogrammable by a clinical user, such as a physician or other caregiverwho treats the patient using system 100. Programming device 102 providesthe user with accessibility to the user-programmable parameters. Invarious embodiments, programming device 102 is configured to becommunicatively coupled to stimulation device 104 via a wired orwireless link.

In various embodiments, programming device 102 includes a user interface110 (e.g., a user interface embodied by a graphical, text, voice, orhardware-based user interface) that allows the user to set and/or adjustvalues of the user-programmable parameters by creating, editing,loading, and removing programs that include parameter combinations suchas patterns and waveforms. These adjustments may also include changingand editing values for the user-programmable parameters or sets of theuser-programmable parameters individually (including values set inresponse to a therapy efficacy indication). Such waveforms may include,for example, the waveform of a pattern of neurostimulation pulses to bedelivered to the patient as well as individual waveforms that are usedas building blocks of the pattern of neurostimulation pulses. Examplesof such individual waveforms include pulses, pulse groups, and groups ofpulse groups. The program and respective sets of parameters may alsodefine an electrode selection specific to each individually definedwaveform.

As described in more detail below with respect to FIGS. 7 to 9, a user,e.g., the patient, or a clinician or other medical professionalassociated with the patient can select, load, modify, and implement oneor more parameters of a defined program for neurostimulation treatment,based on programming determination logic that identifies the parametersusing a trust modeling system and a program modeling system. Based on amodeling of pain, the programming determination logic can determinewhich program or parameter is likely to produce an improvement for apredetermined condition involving chronic pain. Example parameters thatcan be implemented by a selected program include, but are not limited tothe following: amplitude, pulse width, frequency, duration, total chargeinjected per unit time, cycling (e.g., on/off time), pulse shape, numberof phases, phase order, interphase time, charge balance, ramping, aswell as spatial variance (e.g., electrode configuration changes overtime).

As detailed in FIG. 6, a controller, e.g., controller 650 of FIG. 6, canimplement program(s) and parameter setting(s) to implement a specificneurostimulation waveform, pattern, or energy output, using a program orsetting in storage, e.g., external storage device 618 of FIG. 6, orusing settings communicated via an external communication device 620 ofFIG. 6 corresponding to the selected program. The implementation of suchprogram(s) or setting(s) may further define a therapy strength andtreatment type corresponding to a specific pulse group, or a specificgroup of pulse groups, based on the specific program(s) or setting(s).As also described in more detail below with respect to FIG. 7 andthereafter, a program modeling system and pain modeling logic mayoperate to produce this information based on trust dynamics. As alsodescribed, a clinician or the patient may also affect use andimplementation of such programs or settings, including in settings wherea combination of dynamic (automatic) and manual control are involved.

Portions of the stimulation device 104, e.g., implantable medicaldevice, or the programming device 102 can be implemented using hardware,software, or any combination of hardware and software. Portions of thestimulation device 104 or the programming device 102 may be implementedusing an application-specific circuit that can be constructed orconfigured to perform one or more particular functions, or can beimplemented using a general-purpose circuit that can be programmed orotherwise configured to perform one or more particular functions. Such ageneral-purpose circuit can include a microprocessor or a portionthereof, a microcontroller or a portion thereof, or a programmable logiccircuit, or a portion thereof. The system 100 could also include asubcutaneous medical device (e.g., subcutaneous ICD, subcutaneousdiagnostic device), wearable medical devices (e.g., patch based sensingdevice), or other external medical devices.

FIG. 2 illustrates an embodiment of a stimulation device 204 and a leadsystem 208, such as may be implemented in neurostimulation system 100 ofFIG. 1. Stimulation device 204 represents an embodiment of stimulationdevice 104 and includes a stimulation output circuit 212 and astimulation control circuit 214. Stimulation output circuit 212 producesand delivers neurostimulation pulses, including the neurostimulationwaveform and parameter settings implemented via a program selected orimplemented with the user interface 110. Stimulation control circuit 214controls the delivery of the neurostimulation pulses using the pluralityof stimulation parameters, which specifies a pattern of theneurostimulation pulses. Lead system 208 includes one or more leads eachconfigured to be electrically connected to stimulation device 204 and aplurality of electrodes 206 distributed in the one or more leads. Theplurality of electrodes 206 includes electrode 206-1, electrode 206-2, .. . electrode 206-N, each a single electrically conductive contactproviding for an electrical interface between stimulation output circuit212 and tissue of the patient, where N≥2. The neurostimulation pulsesare each delivered from stimulation output circuit 212 through a set ofelectrodes selected from electrodes 206. In various embodiments, theneurostimulation pulses may include one or more individually definedpulses, and the set of electrodes may be individually definable by theuser for each of the individually defined pulses.

In various embodiments, the number of leads and the number of electrodeson each lead depend on, for example, the distribution of target(s) ofthe neurostimulation and the need for controlling the distribution ofelectric field at each target. In one embodiment, lead system 208includes 2 leads each having 8 electrodes. Those of ordinary skill inthe art will understand that the neurostimulation system 100 may includeadditional components such as sensing circuitry for patient monitoringand/or feedback control of the therapy, telemetry circuitry, and power.

The neurostimulation system may be configured to modulate spinal targettissue or other neural tissue. The configuration of electrodes used todeliver electrical pulses to the targeted tissue constitutes anelectrode configuration, with the electrodes capable of beingselectively programmed to act as anodes (positive), cathodes (negative),or left off (zero). In other words, an electrode configurationrepresents the polarity being positive, negative, or zero. Otherparameters that may be controlled or varied include the amplitude, pulsewidth, and rate (or frequency) of the electrical pulses. Each electrodeconfiguration, along with the electrical pulse parameters, can bereferred to as a “modulation parameter” set. Each set of modulationparameters, including fractionalized current distribution to theelectrodes (as percentage cathodic current, percentage anodic current,or off), may be stored and combined into a program that can then be usedto modulate multiple regions within the patient.

The neurostimulation system may be configured to deliver differentelectrical fields to achieve a temporal summation of modulation. Theelectrical fields can be generated respectively on a pulse-by-pulsebasis. For example, a first electrical field can be generated by theelectrodes (using a first current fractionalization) during a firstelectrical pulse of the pulsed waveform, a second different electricalfield can be generated by the electrodes (using a second differentcurrent fractionalization) during a second electrical pulse of thepulsed waveform, a third different electrical field can be generated bythe electrodes (using a third different current fractionalization)during a third electrical pulse of the pulsed waveform, a fourthdifferent electrical field can be generated by the electrodes (using afourth different current fractionalized) during a fourth electricalpulse of the pulsed waveform, and so forth. These electrical fields canbe rotated or cycled through multiple times under a timing scheme, whereeach field is implemented using a timing channel. The electrical fieldsmay be generated at a continuous pulse rate, or as bursts of pulses.Furthermore, the interpulse interval (i.e., the time between adjacentpulses), pulse amplitude, and pulse duration during the electrical fieldcycles may be uniform or may vary within the electrical field cycle.Some examples are configured to determine a modulation parameter set tocreate a field shape to provide a broad and uniform modulation fieldsuch as may be useful to prime targeted neural tissue withsub-perception modulation. Some examples are configured to determine amodulation parameter set to create a field shape to reduce or minimizemodulation of non-targeted tissue (e.g., dorsal column tissue). Variousexamples disclosed herein are directed to shaping the modulation fieldto enhance modulation of some neural structures and diminish modulationat other neural structures. The modulation field may be shaped by usingmultiple independent current control (MICC) or multiple independentvoltage control to guide the estimate of current fractionalization amongmultiple electrodes and estimate a total amplitude that provide adesired strength. For example, the modulation field may be shaped toenhance the modulation of dorsal horn neural tissue and to minimize themodulation of dorsal column tissue. A benefit of MICC is that MICCaccounts for various in electrode-tissue coupling efficiency andperception threshold at each individual contact, so that “hotspot”stimulation is eliminated.

The number of electrodes available combined with the ability to generatea variety of complex electrical pulses, presents a huge selection ofavailable modulation parameter sets to the clinician or patient. Forexample, if the neurostimulation system to be programmed has sixteenelectrodes, millions of modulation parameter value combinations may beavailable for programming into the neurostimulation system. Furthermore,SCS systems may have as many as thirty-two electrodes, whichexponentially increases the number of modulation parameter valuecombinations available for programming. To facilitate such programming,a clinician often initially programs and modifies the modulationparameters through a computerized programming system, to allow themodulation parameters to be established from starting parameter sets(programs) and patient and clinician feedback. In addition, the patientoften is provided with a limited set of controls to switch from a firstprogram to a second program, based on user preferences and thesubjective amount of pain or discomfort that the patient is treating.However, the implementation and use of a program modeling system andpain modeling logic as described further in FIGS. 7 to 9 and thereafterprovides a mechanism for recommending and controlling programs with newcombinations of parameter settings, in a fashion that emphasizescustomization to the patient based on trust dynamics.

FIG. 3 illustrates an embodiment of a programming device 302, such asmay be implemented in neurostimulation system 100. Programming device302 represents an embodiment of programming device 102 and includes astorage device 318, a programming control circuit 316, and a userinterface device 310. Programming control circuit 316 generates theplurality of stimulation parameters that controls the delivery of theneurostimulation pulses according to the pattern of the neurostimulationpulses. The user interface device 310 represents an embodiment toimplement the user interface 110.

In various embodiments, the user interface device 310 includes aninput/output device 320 that is capable to receive user interaction andcommands to load, modify, and implement neurostimulation programs andschedule delivery of the neurostimulation programs. In variousembodiments, the input/output device 320 allows the user to create,establish, access, and implement respective parameter values of aneurostimulation program through graphical selection (e.g., in agraphical user interface output with the input/output device 320),including values of a therapeutic neurostimulation field. In variousexamples, the user interface device 310 can receive user input toinitiate the implementation of the programs which are recommended,modified, selected, or loaded through use of a program modeling system,which are described in more detail below.

In various embodiments, the input/output device 320 allows the patientuser to apply, change, modify, or discontinue certain building blocks ofa program and a frequency at which a selected program is delivered. Invarious embodiments, the input/output device 320 can allow the patientuser to save, retrieve, and modify programs (and program settings)loaded from a clinical encounter, managed from the patient feedbackcomputing device, or stored in storage device 318 as templates. Invarious embodiments, the input/output device 320 and accompanyingsoftware on the user interface device 310 allows newly created buildingblocks, program components, programs, and program modifications to besaved, stored, or otherwise persisted in storage device 318.

In one embodiment, the input/output device 320 includes a touchscreen.In various embodiments, the input/output device 320 includes any type ofpresentation device, such as interactive or non-interactive screens, andany type of user input device that allows the user to interact with auser interface to implement, remove, or schedule the programs, and asapplicable, to edit or modify waveforms, building blocks, and programcomponents. Thus, the input/output device 320 may include one or more ofa touchscreen, keyboard, keypad, touchpad, trackball, joystick, andmouse. In various embodiments, circuits of the neurostimulation system100, including its various embodiments discussed in this document, maybe implemented using a combination of hardware and software. Forexample, the logic of the user interface 110, the stimulation controlcircuit 214, and the programming control circuit 316, including theirvarious embodiments discussed in this document, may be implemented usingan application-specific circuit constructed to perform one or moreparticular functions or a general-purpose circuit programmed to performsuch function(s). Such a general-purpose circuit includes, but is notlimited to, a microprocessor or a portion thereof, a microcontroller orportions thereof, and a programmable logic circuit or a portion thereof.

FIG. 4 illustrates an implantable neurostimulation system 400 andportions of an environment in which system 400 may be used. System 400includes an implantable system 422, an external system 402, and atelemetry link 426 providing for wireless communication between animplantable system 422 and an external system 402. Implantable system422 is illustrated in FIG. 4 as being implanted in the patient's body499. The system is illustrated for implantation near the spinal cord.However, the neuromodulation system may be configured to modulate otherneural targets.

Implantable system 422 includes an implantable stimulator 404 (alsoreferred to as an implantable pulse generator, or IPG), a lead system424, and electrodes 406, which represent an embodiment of thestimulation device 204, the lead system 208, and the electrodes 206,respectively. The external system 402 represents an embodiment of theprogramming device 302.

In various embodiments, the external system 402 includes one or moreexternal (non-implantable) devices each allowing the user and/or thepatient to communicate with the implantable system 422. In someembodiments, the external system 402 includes a programming deviceintended for the user to initialize and adjust settings for theimplantable stimulator 404 and a remote control device intended for useby the patient. For example, the remote control device may allow thepatient to turn the implantable stimulator 404 on and off and/or adjustcertain patient-programmable parameters of the plurality of stimulationparameters. The remote control device may also provide a mechanism toreceive and process feedback on the operation of the implantableneuromodulation system. Feedback may include metrics or an efficacyindication reflecting perceived pain, effectiveness of therapies, orother aspects of patient comfort or condition. Such feedback may beautomatically detected from a patient's physiological state, or manuallyobtained from user input entered in a user interface.

For the purposes of this specification, the terms “neurostimulator,”“stimulator,” “neurostimulation,” and “stimulation” generally refer tothe delivery of electrical energy that affects the neuronal activity ofneural tissue, which may be excitatory or inhibitory; for example byinitiating an action potential, inhibiting or blocking the propagationof action potentials, affecting changes inneurotransmitter/neuromodulator release or uptake, and inducing changesin neuro-plasticity or neurogenesis of tissue. It will be understoodthat other clinical effects and physiological mechanisms may also beprovided through use of such stimulation techniques.

FIG. 5 illustrates an embodiment of the implantable stimulator 404 andthe one or more leads 424 of an implantable neurostimulation system,such as the implantable system 422. The implantable stimulator 404 mayinclude a sensing circuit 530 that is optional and required only whenthe stimulator has a sensing capability, stimulation output circuit 212,a stimulation control circuit 514, an implant storage device 532, animplant telemetry circuit 534, and a power source 536. The sensingcircuit 530, when included and needed, senses one or more physiologicalsignals for purposes of patient monitoring and/or feedback control ofthe neurostimulation. Examples of the one or more physiological signalsincludes neural and other signals each indicative of a condition of thepatient that is treated by the neurostimulation and/or a response of thepatient to the delivery of the neurostimulation.

The stimulation output circuit 212 is electrically connected toelectrodes 406 through the one or more leads 424, and delivers each ofthe neurostimulation pulses through a set of electrodes selected fromthe electrodes 406. The stimulation output circuit 212 can implement,for example, the generating and delivery of a customizedneurostimulation waveform (e.g., implemented from a parameter of aprogram selected with the present dynamic model or dynamical informationsystem) to an anatomical target of a patient.

The stimulation control circuit 514 represents an embodiment of thestimulation control circuit 214 and controls the delivery of theneurostimulation pulses using the plurality of stimulation parametersspecifying the pattern of the neurostimulation pulses. In oneembodiment, the stimulation control circuit 514 controls the delivery ofthe neurostimulation pulses using the one or more sensed physiologicalsignals and processed input from patient feedback interfaces. Theimplant telemetry circuit 534 provides the implantable stimulator 404with wireless communication with another device such as a device of theexternal system 402, including receiving values of the plurality ofstimulation parameters from the external system 402. The implant storagedevice 532 stores values of the plurality of stimulation parameters,including parameters from one or more programs obtained using thepatient feedback and the programming modification logic techniquesdisclosed herein.

The power source 536 provides the implantable stimulator 404 with energyfor its operation. In one embodiment, the power source 536 includes abattery. In one embodiment, the power source 536 includes a rechargeablebattery and a battery charging circuit for charging the rechargeablebattery. The implant telemetry circuit 534 may also function as a powerreceiver that receives power transmitted from external system 402through an inductive couple.

In various embodiments, the sensing circuit 530 (if included), thestimulation output circuit 212, the stimulation control circuit 514, theimplant telemetry circuit 534, the implant storage device 532, and thepower source 536 are encapsulated in a hermetically sealed implantablehousing. In various embodiments, the lead(s) 424 are implanted such thatthe electrodes 406 are placed on and/or around one or more targets towhich the neurostimulation pulses are to be delivered, while theimplantable stimulator 404 is subcutaneously implanted and connected tothe lead(s) 424 at the time of implantation.

FIG. 6 illustrates an embodiment of an external patient programmingdevice 602 of an implantable neurostimulation system, such as theexternal system 402, with the external patient programming device 602illustrated to receive commands (e.g., program selections, information)directly or indirectly from a program modeling system (not shown in FIG.6, but discussed with reference to FIGS. 7 to 9, below). The externalpatient programming device 602 represents an embodiment of theprogramming device 302, and includes an external telemetry circuit 640,an external storage device 618, a programming control circuit 616, auser interface device 610, a controller 650, and an externalcommunication device 620.

The external telemetry circuit 640 provides the external patientprogramming device 602 with wireless communication to and from anothercontrollable device such as the implantable stimulator 404 via thetelemetry link 426, including transmitting one or a plurality ofstimulation parameters (including changed stimulation parameters of aselected program) to the implantable stimulator 404. In one embodiment,the external telemetry circuit 640 also transmits power to theimplantable stimulator 404 through inductive coupling.

The external communication device 620 provides a mechanism to conductcommunications with a programming information source, such as a dataservice, program modeling system, or other aspects of a dynamicinformation system, to receive program information via an externalcommunication link (not shown). As described in the followingparagraphs, the program modeling system may be used to identify aprogram or program data to the external patient programming device 602that corresponds to a new or different neurostimulation program orcharacteristics of a neurostimulation program (which is, in turn,selected to provide an improved treatment of a chronic pain condition bythe dynamic model). The external communication device 620 and theprogramming information source may communicate using any number of wiredor wireless communication mechanisms described in this document,including but not limited to IEEE 802.11 (Wi-Fi), Bluetooth, Infrared,and like standardized and proprietary wireless communicationsimplementations. Although the external telemetry circuit 640 and theexternal communication device 620 are depicted as separate componentswithin the external patient programming device 602, the functionality ofboth of these components may be integrated into a single communicationchipset, circuitry, or device.

The external storage device 618 stores a plurality of existingneurostimulation waveforms, including definable waveforms for use as aportion of the pattern of the neurostimulation pulses, settings andsetting values, other portions of a program, and related treatmentefficacy indication values. In various embodiments, each waveform of theplurality of individually definable waveforms includes one or morepulses of the neurostimulation pulses, and may include one or more otherwaveforms of the plurality of individually definable waveforms. Examplesof such waveforms include pulses, pulse blocks, pulse trains, and traingroupings, and programs. The existing waveforms stored in the externalstorage device 618 can be definable at least in part by one or moreparameters including, but not limited to the following: amplitude, pulsewidth, frequency, duration(s), electrode configurations, total chargeinjected per unit time, cycling (e.g., on/off time), waveform shapes,spatial locations of waveform shapes, pulse shapes, number of phases,phase order, interphase time, charge balance, and ramping.

The external storage device 618 also stores a plurality of individuallydefinable fields that may be implemented as part of a program. Eachwaveform of the plurality of individually definable waveforms isassociated with one or more fields of the plurality of individuallydefinable fields. Each field of the plurality of individually definablefields is defined by one or more electrodes of the plurality ofelectrodes through which a pulse of the neurostimulation pulses isdelivered and a current distribution of the pulse over the one or moreelectrodes. A variety of settings in a program (including settingschanged as a result of evaluation with the dynamical information systemand the dynamic models) may be correlated to the control of thesewaveforms and definable fields.

The programming control circuit 616 represents an embodiment of aprogramming control circuit 316 and generates the plurality ofstimulation parameters, which is to be transmitted to the implantablestimulator 404, based on the pattern of the neurostimulation pulses. Thepattern is defined using one or more waveforms selected from theplurality of individually definable waveforms (e.g., defined by aprogram) stored in an external storage device 618. In variousembodiments, a programming control circuit 616 checks values of theplurality of stimulation parameters against safety rules to limit thesevalues within constraints of the safety rules. In one embodiment, thesafety rules are heuristic rules.

The user interface device 610 represents an embodiment of the userinterface device 310 and allows the user (including a patient orclinician) to select, modify, enable, disable, activate, schedule, orotherwise define a program or sets of programs for use with theneurostimulation device and perform various other monitoring andprogramming tasks for operation of the neurostimulation device. The userinterface device 610 can enable a user to implement, save, persist, orupdate a program including the program or program parameters recommendedor indicated by the programming information source, such as a dataservice or program modeling system. The user interface device 610includes a display screen 642, a user input device 644, and an interfacecontrol circuit 646. The display screen 642 may include any type ofinteractive or non-interactive screens, and the user input device 644may include any type of user input devices that supports the variousfunctions discussed in this document, such as a touchscreen, keyboard,keypad, touchpad, trackball, joystick, and mouse. The user interfacedevice 610 may also allow the user to perform any other functionsdiscussed in this document where user interface input is suitable.

Interface control circuit 646 controls the operation of the userinterface device 610 including responding to various inputs received bythe user input device 644 that define or modify characteristics ofimplementation (including conditions, schedules, and variations) of oneor more programs, parameters within the program, characteristics of oneor more stimulation waveforms within a program, and like neurostimulatoroperational values that may be entered or selected with the externalpatient programming device 602, or obtained from the programminginformation source, such as the data service, or the program modelingsystem. Interface control circuit 646 includes a neurostimulationprogram circuit 660 that may generate a visualization of suchcharacteristics of implementation, and receive and implement commands toimplement the program and the neurostimulator operational values(including a status of implementation for such operational values).These commands and visualization may be performed in a review andguidance mode, status mode, or in a real-time programming mode.

The controller 650 can be a microprocessor that communicates with theexternal telemetry circuit 640, the external communication device 620,the external storage device 618, the programming control circuit 616,and the user interface device 610, via a bidirectional data bus. Thecontroller 650 can be implemented by other types of logic circuitry(e.g., discrete components or programmable logic arrays) using a statemachine type of design. As used in this disclosure, the term “circuitry”should be taken to refer to either discrete logic circuitry, firmware,or to the programming of a microprocessor.

As will be understood, the variety of settings for a neurostimulationdevice may be provided by many variations of programming parametersettings within programs. Existing patient programmers only provide alimited ability for a patient to cycle through programs that havedefined programming parameters, with hundreds or thousands of specificsettings often being rolled up into a single program. The followingsystem and methods provide technical mechanisms to generate andrecommend new programs and parameters for chronic pain therapy inresponse to trust dynamics and observed trust characteristics. Based onthe identification of trust measurements and pain susceptibility, theassessment of pain susceptibility can be leveraged to further tailor thedelivery of neurostimulation settings to improve treatment for pain.

In an example, the trust measurements and pain susceptibility values aredetermined through the use of a chatbot or other automated/computeragent designed to engage a patient on a regular basis in interactions(e.g., person-to-agent communications). This chatbot is used toestablish commitments with the patient, from which expectations andchanges can be measured as a result of the fulfillment or violation ofindividual commitments or sets of commitments.

A variety of academic research has been conducted on understandinginteractions between parties and estimating trust as a result of suchinteractions. Research has shown that a computational model of trustbased on commitments may be utilized to determine the trust of one partyrelative to another, based on the interactions between the parties. Inparticular, commitments provide an important way to measure trustbecause such commitments can be easily identified from interpersonalinteractions (by an objective outside observer) and can be used toeasily classify or characterize the outcomes of interactions inhigh-level terms.

A simple example of a commitment used in a trust determination setting,provided in Kalia et al., Güven: estimating trust from communications,JOURNAL OF TRUST MANAGEMENT (2016) 3:1, is as follows: “A commitmentC(debtor, creditor, antecedent, consequent) means that the debtorcommits to bringing about the consequent for the creditor provided theantecedent holds. For example, C(Buck, Selia, deliver, pay) means thatBuck (buyer) commits to Selia (seller) to paying a specified amountprovided Selia delivers the goods. When Selia delivers, the commitmentis detached. When Buck pays, the commitment is discharged or satisfied.If Selia delivers but Buck does not pay, the commitment is violated. Inessence, a commitment describes a social relationship between twopersons giving a high-level description of what one expects of theother. As a result, it is natural that commitments (and theirsatisfaction or violation) be useful as a basis for trust. In thisexample, if Buck discharges the commitment, he brings a positiveexperience to Selia and Selia's trust for Buck may increase; if Buckviolates the commitment, he brings a negative experience to Selia andSelia's trust for Buck may decrease.”

This commitment progression, and the results of creating, detaching,discharging, and canceling a commitment (and resulting fulfillments orviolations of such a commitment) may be observed from variouscommunications between a patient and another party (an agent) for thetrust dynamics and pain management purposes described herein. Theparticular commitments and interactions that occur between the patientand the other party need not, however, discuss the neurostimulationmedical treatment or pain condition of the patient. As a result,interactions and commitments may be made regarding topics that areentirely unrelated to neurostimulation or pain, even as the results ofsuch interactions and commitments are observed to determine a trustcondition used for neurostimulation treatment.

The relationship between trust and pain perception in a particularpatient (and pain susceptibility, and the receptibility of analgesictreatment with neurostimulation) may be determined as a result of acognitive disposition to trust from many patients. Specifically, whethera particular patient exhibits a level of trust—and the amount of trustthat they exhibit towards a particular party, as contrasted with anamount of hostility or rejection—may be used as a derivative measurementor indicator for the potential efficacy of analgesic effect with aneurostimulation treatment. As a result, the tracking of a trustmeasurement value in time can be used longitudinally, or at crosssectional points, to optimize treatments and to determine whether thetreatment is working, whether the treatment provides a beneficialresult, or whether the treatment can be increased or modified to provideadditional or more suitable amounts of treatment.

In a specific example, the trust measurement value discussed herein maybe represented as an overall level or ratio of positive to negativeoutcomes. For instance, this trust measurement value may be mapped tocommitment outcomes with the use of a ratio, defined as:(Positive)/(Positive+Negative), which defines a trust measurement valueas a percentage of total interactions. In a specific example, a positiveexperience is defined as when an agent (e.g., chatbot) creates acommitment with the human subject, and the agent satisfies thecommitment; whereas a negative experience is defined as when the agentviolates the commitment to the human subject. In still further specificexamples, the trust measurement value may be computed and weighted basedon how severe the violation is, including by tracking the value relativeto a base trust value or metric. Accordingly, the goal of the trustmeasurement value is to provide a measurement of the state of trustingof a particular human subject, as a feedback mechanism to estimate theparticular suitability or benefit of a neurostimulation treatment ortreatment change.

The following drawings illustrate example implementations of systemsutilizing these or similar trust dynamics for the purpose of chronicpain treatment. It will be understood that variations to the pain andtrust determination examples listed above, as used for the treatment ofchronic pain with neurostimulation programs, are within the scope of thepresent disclosure.

FIG. 7 illustrates, by way of example, an embodiment of datainteractions among a patient interaction computing device 710, a programmodeling system 720, a programming device 602, and a data service 770for selecting and implementing respective programs of defined parametersettings of a neurostimulation device, in connection with trust dynamicsused to identify and deploy chronic pain treatments. The programmodeling system 720 is shown in FIG. 7 in the form of a computing device(e.g., a server) with the computing device being specially programmed tocommunicate, over a network, the results of the modeled parametersettings and/or programs.

In an example, such program modeling may be performed through theevaluation of trust and pain values and settings, such as performedwith: a trust measurement classifier 724 (e.g., with an algorithmimplemented in software that is executed on the computing device toextract, identify, and determine a trust measurement value from patientinteraction data); a trust graph 726 (e.g., with a data structureadapted to track and predict trust measurement values of a patient overtime); and pain modeling logic 728 (e.g., with an algorithm implementedin software that is executed to determine the particular level of painor pain susceptibility by the patient, based on the trust measurement orother trust values). The program modeling system 720 may also include auser interface 722 (e.g., in a software app interface, or an applicationprogramming interface) which provides the results of the trustmeasurement or pain measurements to another system or to a human user.It will be understood that other form factors and embodiments of theprogram modeling system 720, including in the integration of otherprogramming devices, data services, or information services, may also bedeployed.

In an example, the patient interaction computing device 710 is acomputing device (e.g., personal computer, tablet, smartphone) or otherform of user-interactive device (e.g., robot, AI device) which receivesand provides interaction with a patient using a graphical user interface712 and interaction logic 714. The specific outputs provided via thegraphical user interface 712 may be defined and determined using theinteraction logic 714, such as to facilitate various human-to-machineinteractions in a communication session. Other form factors andinterfaces such as smart speakers, audio interfaces, text interfaces,and the like may also be substituted for or augmented with the graphicaluser interface 712. In an example, the interaction logic 714 hosts oneor more conversations with the patient using the graphical userinterface 712, with such conversations involving the establishment,fulfillment, or violation of commitments and other trust-relatedinteractions. Also in an example, the interaction logic 714 may beexposed by or host a chatbot or agent-based interface, through the useof the graphical user interface 712.

The program modeling system 720 (and in some examples, the programmingdevice 602) may communicate to a data service 770 via a network 740(e.g., a private local area network, public wide area network, theInternet, and the like) to obtain pre-defined programs, programsettings, program modifications, constraints, rules, or like informationrelated to programming (programs and parameters 776) or systemoperational data (e.g., interaction data 778). Such system operationaldata may be related to trust dynamics, trust measurement, painsusceptibility, and pain modeling for the particular patient or a set ofpatients. The data service 770, for example, may serve as a data serviceto host program information for a plurality of neurostimulation programs(e.g., across multiple patients, facilities, or facility locations) andmodel parameters. In an example, the data service 770 may be operated orhosted by a research institution, medical service provider, or a medicaldevice provider (e.g., a manufacturer of the neurostimulation device)for managing data and settings for respective programs and parameters776 and interaction data 778 among a plurality of clinical deploymentsor device types. The data service 770 may provide an interface tobackend data components such as a data processing server 772 and adatabase 774, to host, track, and maintain a plurality of programs andparameters 776 and interaction data 778 and related settings. Forinstance, the programming data service 770 may be accessed using anapplication programming interface (API) or other remotely accessibleinterface accessible via the network 740.

In an example, program parameters 752 to update the parameter(s) orprogram(s) of the neurostimulation device 750 are generated, identified,or otherwise determined by the program modeling system 720, and thencommunicated to the neurostimulation device 750 by the programmingdevice 602. In a further example, the pain modeling logic 728 of theprogram modeling system 720 results in selection of an entirely newprogram, or a customized or modified program, which is communicated inthe program parameters 752. In this fashion, the programming device 602may comprise a patient or clinician programmer device, which is operablewith the user interface 732 and program implementation logic 734 toactivate, deploy, select, define, edit, and modify parameter(s) orprogram(s) in a personal, home, clinical, or experimental setting.Finally, in some examples, the program parameters 752 may be directlycommunicated or activated from the program modeling system 720 ratherthan a programming device 602. The programming device 602 is illustratedin the form factor of a patient-operable remote control, but may beembodied in a number of other form factors, including inclinician-operated systems.

FIG. 8 illustrates, by way of example, a block diagram 800 of anembodiment of functional components and data sets used in selecting andimplementing respective analgesic parameter settings for operation of aneurostimulation device based on trust dynamics. As shown, the blockdiagram 800 illustrates data flows among a series of sequentialprocessing actions (810, 820, 830, 840, 850, 860) discussed below,followed by programming actions (870, 880) and operational actions (890,895). It will be understood that these sequential actions may occur inthe context of operations performed among the program modeling system720, patient interaction computing device 710, and programming device602, as referenced in FIG. 7 above, which identifies appropriate programparameters and settings for the neurostimulation device 750 using trustdynamics. However, the operations may be implemented in other settingsand with other models, and accordingly, other data and processing flowsmay occur with variations of trust dynamics as described herein.

The sequential processing actions are depicted as commencing with userinteractions 810, which are used to establish user-party commitments 820involving aspects of trust fulfillment or violation. As discussed above,these user interactions and user-party commitments 820 may occur as aresult of agent-user communications 812 with a chatbot (e.g., asprovided in a graphical user interface 712 on the patient interactioncomputing device 710). The results of the commitments are used toproduce a trust measurement value 830 or other trust representation.

In an example, the trust measurement value 830 is represented as a valuebetween 0 to 1. In some examples, this value is scaled to 0 to 1,rounded up or down, or represented in another form. The trustmeasurement value 830 may be determined as a result of a trustmeasurement classifier 724 which predicts trust levels and classifiesrelevant inputs (e.g., commitment results and reactions, userinteraction results) according to a trained or predetermined model. Thetrust measurement value 830 may also be represented in the context ofthe trust graph 726, which allows a state of trust to change and adaptover a period of time according to known values.

The trust measurement value 830 may be provided for further analysis toproduce a pain susceptibility measurement value 840. This painsusceptibility measurement value 840 may be derived or a function of thetrust measurement value 830 exclusively or as a result of otherphysiological data and observations. In a further example, the painsusceptibility measurement value 840 is enhanced as a result of aneuroimaging procedure that produces neuroimaging procedure data 842,such as medical imaging which is used to predict response to pain,treatment response, placebo effect, or which otherwise shows or predictsthe effects of ongoing pain or neurostimulation relief. For example, aplacebo effect measurement may be used to validate whether the trustmetric has provided a proper prediction of treatment or treatmentresults.

The pain susceptibility measurement value 840 may be produced intotreatment objectives 850 which may comprise or indicate various paintreatment approaches, areas for projected treatment, or othertreatment-based indications relevant to the particular patient. Thetreatment objectives 850 may be further determined as a result of painmeasurements 844 or other pain-related indications from the neuroimagingprocedure data 842. Thus, the treatment objectives 850 may be producedas a result of pain modeling logic 728 which in turn may be correlatedto any number of program modeling operations.

As a result of the treatment objectives 850, the pain modeling logic 728may produce various types of analgesic stimulation parameter adjustmentsor values 860. These parameters in turn may be correlated to theselection or modification of a particular program that causes theneurostimulation device to implement the adjustments or values forimproving analgesic effect in a patient. In some examples, theparticular adjustments or values are tied to constraints and conditionssuch as safety or regulatory operation conditions, device engineering oroperational limits, comfort or preference settings, or the like.Ultimately, the result of device programming 880 causes the selected ormodified program or parameter to modify neurostimulation deviceoperation 890.

In further examples, subsequent operation of the device, treatment, andtrust dispositions may be used to coordinate user feedback 895 andfurther refinement of the neurostimulation parameters or program. As aresult, the user feedback 895 (or other forms of monitoring) may modifythe subsequent parameters of stimulation delivery based on a subsequentmeasure of trust disposition through subsequent user interactions 810and subsequent agent-user communications 812. The user feedback 895 mayalso supply relevant values for a pain measurement or painsusceptibility measurement value 840. For instance, in some examples,the user feedback 895 may provide a feedback loop for a daily, weekly,or other regular monitoring and adjustment of neurostimulation.

The user feedback 895 may also be coordinated with physician-patientcommunications 814 as part of clinician oversight of the treatmentprocess. In some examples, the physician-user communications 814 orother clinician oversight is used to affect or facilitate the userinteractions 810, the pain susceptibility measurement value 840, thetreatment objectives 850, or other variations in treatment and parameterdetermination.

FIG. 9 illustrates, by way of example, an embodiment of a data andcontrol flow 900 among trust modeling operations (with trust modelinglogic 902) and neurostimulation program modeling (in a program modelinglogic 920) operations, used in selecting and implementing respectiveanalgesic parameter settings for operation of the neurostimulationdevice (e.g., the neurostimulation device 750) based on trust dynamics.As illustrated, the data and control flow 900 may involve a plurality ofinputs 904 that are received, and a plurality of outputs 906 which areconsidered as part of the trust modeling logic 902. The results of theseinputs and outputs are processed with the use of a trust dynamical model908 that considers trust dynamics and measurements for use inneurostimulation programming and treatment.

In an example, the inputs 904 received within the trust modeling logicinclude sensor data 904-1 (e.g., physiological data from theneurostimulator device, or other medical monitoring devices) and trustcondition data 904-2 (e.g., results, measurements, or values produced asa result of trust commitment violations and fulfillments). As suggestedabove, a user interface 910 may implement or be controlled by aspects ofthe trust modeling logic 902 to receive and facilitate thecommitment-based interactions 912. The results of these interactions andthe inputs 904 may be used to produce the outputs 906 including a trustmeasurement value 906-1, one or more program setting representations906-2, and like values.

In an example, the program modeling logic 920 utilizes the results ofthe trust dynamical model 908 and other inputs and outputs from thetrust modeling logic 902, to perform aspects of program selection 922,program modification 926, and other operational changes. Such modelinglogic may involve use of an adjustment algorithm 924 which specificallyis designed or modeled to implement changes based on the trust dynamicsor other relevant trust modeling considerations.

As suggested above, the output of the programming modeling logic 920 mayidentify and effect the use of programming parameters 930 (e.g., deviceprogramming 880, and/or device program selection/modification 870) aspart of treatment for a chronic pain condition using theneurostimulation device 750. As illustrated, the programming parameters930 may include defined aspects such as amplitude, pulse type, pulsepattern, duration, and frequency, among other aspects described herein.The results of the definition and adjustment to the programmingparameters 930 may result in specific analgesic effect stimulation 940provided by the neurostimulation device. The results of thisneurostimulation, and the feedback from this neurostimulation, may befurther modified and updated in connection with the program modelinglogic 920, trust modeling logic 902, and other system components orfunctions discussed above.

FIG. 10 illustrates, by way of example, an embodiment of a processingmethod 1000 implemented by a system or device for use to adjustprogramming of an implantable electrical neurostimulation device basedon trust dynamics. For example, the processing method 1000 can beembodied by electronic operations performed by one or more computingsystems or devices that are specially programmed to implement the trustmeasurement, program modeling, and neurostimulation programmingfunctions described herein. In specific examples, the operations of themethod 1000 may be implemented through the systems and data flowsdepicted above in FIGS. 7 to 9.

In an example, the method 1000 includes the capturing (e.g., receiving,requesting, extracting, processing) of interactions with a human subject(e.g., patient) involving one or more commitments and user activities(operation 1002). This may be followed by the performing of analysis ofinteractions between the human subject and another entity to determinethe results of the one or more commitments (operation 1004). Suchcommitments may include those occurring from agent-user communicationsin a chatbot as discussed above for FIG. 8, although other communicationformats and data forms may also be may be used. In an example, theinteractions are performed with text or voice conversations occurringbetween the human subject and the another entity. For instance, theanother entity may have created the commitment with the human subjectand performed at least one observable action to cause the fulfillment orthe violation of the at least one commitment.

As a result of the interactions and the analysis, a trust measurementvalue may be determined from the commitments (operation 1006). Thistrust measurement value may be derived or calculated from results of theone or more commitments (such as a reaction to a violation orfulfillment of the commitment) made with a human subject. In an example,the trust measurement value is derived from a reaction of the humansubject in the interactions to specific fulfillment or violation eventsin the one or more commitments. Also in an example, the trustmeasurement value is determined with a classifier that performs analysisof the plurality of interactions for the fulfillment or the violation ofthe at least one commitment, such as with a classifier that is trainedto predict a trust disposition for the human subject towards an otherentity during the interactions. Also in an example, the trustmeasurement value is representable as a value within a trust graph, suchthat the trust graph provides a measurement of trust between the humansubject and the other entity, based on evaluation of the human subjectwith the plurality of interactions over a period of time

The method 1000 continues with a determination of a modification of atleast one neurostimulation programming parameter of the implantableneurostimulation device, based on the trust measurement value (operation1008). In an example, an amount of the modification of theneurostimulation programming parameter from a first state to a secondstate is correlated to an amount of change in the trust measurementvalue from a first state to a second state. In further examples (notdepicted in the method 1000), the determination of the modificationinvolves the use of other intermediate values, such as a painsusceptibility value based on the trust measurement value. For instance,a pain susceptibility value may be based on a prediction of the trustdisposition for the human subject towards the other entity, with thepain susceptibility being used to determine the appropriate amount ortype of programming modification. In further examples, this painsusceptibility is derived from a neuroimaging procedure performed on thehuman subject, such as with neuroimaging data that is used to determinea baseline to predict a placebo response of modification of aneurostimulation programming parameter.

The method 1000 concludes with the implementation of the modifiedneurostimulation programming parameters (operation 1010), such as withprogramming instructions, commands, or settings that cause aneurostimulation device to implement the parameters. Such parameters mayimplement or cause a change for one or more of: pulse patterns, pulseshapes, a spatial location of pulses, waveform shapes, or a spatiallocation of waveform shapes, for modulated energy provided with aplurality of leads of the implantable neurostimulation device. Suchprogramming may be implemented in the manner as described with FIG. 7above, or with other variations involving the use of patient, clinician,or administrator involvement.

Further operations and feedback as part of the method 1000 may continuewith the estimation of subsequent trust measurements and parametermodifications (operation 1012), including the repeating of theoperations 1002-1010 for a subsequent trust measurement value andparameter. In a specific example, the subsequent trust measurementmetric may be determined from a series of interactions with the humansubject conducted after the modification of the at least oneneurostimulation programming parameter, and the subsequent modificationand use of a programming parameter determined from the subsequent trustmeasurement metric.

FIG. 11 illustrates, by way of example, a block diagram of an embodimentof a system 1100 (e.g., a computing system) implementing datameasurement determination circuitry for use to adjust programming of animplantable electrical neurostimulation device for treating pain of ahuman subject. The system 1100 may be a remote control device, patientprogrammer device, clinician programmer device, program modeling system,or other external device, usable for the adjustment of neurostimulationprogramming with the trust dynamic features discussed herein. In someexamples, the system 1100 may be a networked device connected via anetwork (or combination of networks) to a programming device orprogramming service using a communication interface 1108, with theprogramming device or programming service providing output content forthe graphical user interface or responding to input of the graphicaluser interface. The network may include local, short-range, orlong-range networks, such as Bluetooth, cellular, IEEE 802.11 (Wi-Fi),or other wired or wireless networks.

The system 1100 includes a processor 1102 and a memory 1104, which canbe optionally included as part of data measurement processing circuitry1106. The processor 1102 may be any single processor or group ofprocessors that act cooperatively. The memory 1104 may be any type ofmemory, including volatile or non-volatile memory. The memory 1104 mayinclude instructions, which when executed by the processor 1102, causethe processor 1102 to implement the features of the user interface, orto enable other features of the data measurement processing circuitry1106. Thus, electronic operations in the system 1100 may be performed bythe processor 1102 or the circuitry 1106.

For example, the processor 1102 or circuitry 1106 may implement any ofthe features of the method 1000 (including operations 1002, 1004, 1006,1012) to obtain and process data related to trust or pain state of ahuman subject, such as to determine a trust measurement value fromresults of at least one commitment made with a human subject, anddetermine a pain susceptibility value from such trust measurements or atleast one commitment, as part of trust dynamics evaluated for aneurostimulation program or treatment. The system 1100 may save, output,or cause implementation of these measurements, directly or indirectly.It will be understood that the processor 1102 or circuitry 1106 may alsoimplement other aspects of the logic and processing described above withreference to FIGS. 7-9.

FIG. 12 illustrates, by way of example, a block diagram of an embodimentof a system 1200 (e.g., a computing system) implementingneurostimulation programming circuitry 1206 for use to adjustprogramming of an implantable electrical neurostimulation device fortreating pain of a human subject. The system 1200 may be operated by aclinician, a patient, a caregiver, a medical facility, a researchinstitution, a medical device manufacturer or distributor, and embodiedin a number of different computing platforms. The system 1200 may be aremote control device, patient programmer device, program modelingsystem, or other external device, including a regulated device used todirectly implement programming commands and modification with aneurostimulation device. In some examples, the system 1200 may be anetworked device connected via a network (or combination of networks) toa computing system operating a user interface computing system using acommunication interface 1208. The network may include local,short-range, or long-range networks, such as Bluetooth, cellular, IEEE802.11 (Wi-Fi), or other wired or wireless networks.

The system 1200 includes a processor 1202 and a memory 1204, which canbe optionally included as part of neurostimulation programming circuitry1206. The processor 1202 may be any single processor or group ofprocessors that act cooperatively. The memory 1204 may be any type ofmemory, including volatile or non-volatile memory. The memory 1204 mayinclude instructions, which when executed by the processor 1202, causethe processor 1202 to implement the features of the neurostimulationprogramming circuitry 1206. Thus, the following references to electronicoperations in the system 1200 may be performed by the processor 1202 orthe circuitry 1206.

For example, the processor 1202 or circuitry 1206 may implement any ofthe features of the method 1000 (including operations 1008, 1010) todetermine modification of neurostimulation programming parameters,implement (e.g., save, persist, activate, control) the programmingparameters in the neurostimulation device, with use of aneurostimulation device interface 1210. The processor 1202 or circuitry1206 may further provide data and commands to assist the processing andimplementation of the programming using communication interface 1208. Itwill be understood that the processor 1202 or circuitry 1206 may alsoimplement other aspects of the programming devices and device interfacesdescribed above with reference to FIGS. 7-9.

FIG. 13 is a block diagram illustrating a machine in the example form ofa computer system 1300, within which a set or sequence of instructionsmay be executed to cause the machine to perform any one of themethodologies discussed herein, according to an example embodiment. Inalternative embodiments, the machine operates as a standalone device ormay be connected (e.g., networked) to other machines. In a networkeddeployment, the machine may operate in the capacity of either a serveror a client machine in server-client network environments, or it may actas a peer machine in peer-to-peer (or distributed) network environments.The machine may be a personal computer (PC), a tablet PC, a hybridtablet, a personal digital assistant (PDA), a mobile telephone, animplantable pulse generator (IPG), an external remote control (RC), aUser's Programmer (CP), or any machine capable of executing instructions(sequential or otherwise) that specify actions to be taken by thatmachine. Further, while only a single machine is illustrated, the term“machine” shall also be taken to include any collection of machines thatindividually or jointly execute a set (or multiple sets) of instructionsto perform any one or more of the methodologies discussed herein.Similarly, the term “processor-based system” shall be taken to includeany set of one or more machines that are controlled by or operated by aprocessor (e.g., a computer) to individually or jointly executeinstructions to perform any one or more of the methodologies discussedherein.

Example computer system 1300 includes at least one processor 1302 (e.g.,a central processing unit (CPU), a graphics processing unit (GPU) orboth, processor cores, compute nodes, etc.), a main memory 1304 and astatic memory 1306, which communicate with each other via a link 1308(e.g., bus). The computer system 1300 may further include a videodisplay unit 1310, an alphanumeric input device 1312 (e.g., a keyboard),and a user interface (UI) navigation device 1314 (e.g., a mouse). In oneembodiment, the video display unit 1310, input device 1312 and UInavigation device 1314 are incorporated into a touch screen display. Thecomputer system 1300 may additionally include a storage device 1316(e.g., a drive unit), a signal generation device 1318 (e.g., a speaker),a network interface device 1320, and one or more sensors (not shown),such as a global positioning system (GPS) sensor, compass,accelerometer, or other sensor. It will be understood that other formsof machines or apparatuses (such as PIG, RC, CP devices, and the like)that are capable of implementing the methodologies discussed in thisdisclosure may not incorporate or utilize every component depicted inFIG. 13 (such as a GPU, video display unit, keyboard, etc.).

The storage device 1316 includes a machine-readable medium 1322 on whichis stored one or more sets of data structures and instructions 1324(e.g., software) embodying or utilized by any one or more of themethodologies or functions described herein. The instructions 1324 mayalso reside, completely or at least partially, within the main memory1304, static memory 1306, and/or within the processor 1302 duringexecution thereof by the computer system 1300, with the main memory1304, static memory 1306, and the processor 1302 also constitutingmachine-readable media.

While the machine-readable medium 1322 is illustrated in an exampleembodiment to be a single medium, the term “machine-readable medium” mayinclude a single medium or multiple media (e.g., a centralized ordistributed database, and/or associated caches and servers) that storethe one or more instructions 1324. The term “machine-readable medium”shall also be taken to include any tangible (e.g., non-transitory)medium that is capable of storing, encoding or

What is claimed is:
 1. A device for use to adjust programming of animplantable electrical neurostimulation device for treating pain, thedevice comprising: at least one processor and at least one memory; datameasurement processing circuitry, operable with the processor and thememory, the data measurement processing circuitry configured todetermine a trust measurement value from results of a plurality ofinteractions having previously occurred between at least one entity anda human subject, the plurality of interactions having caused at leastone commitment to be made between the at least one entity and the humansubject, wherein the trust measurement value is determined based on theat least one commitment that is made between the at least one entity andthe human subject; neurostimulation programming circuitry, in operationwith the at least one processor and the at least one memory, configuredto: determine a modification of at least one neurostimulationprogramming parameter of the implantable neurostimulation device, basedon the trust measurement value determined from the results of theplurality of interactions; and provide programming instructions to theimplantable neurostimulation device, the programming instructions tocause the implantable neurostimulation device to implement themodification of the at least one neurostimulation programming parameterand provide pain treatment to the human subject with neurostimulationusing the at least one neurostimulation parameter.
 2. The device ofclaim 1, the data measurement processing circuitry further configuredto: determine the trust measurement value from a reaction of the humansubject to a fulfillment or a violation of the at least one commitment;wherein the trust measurement value is determined with a classifier thatperforms analysis of the plurality of interactions for the fulfillmentor the violation of the at least one commitment, and wherein theclassifier is trained to predict a trust disposition for the humansubject towards an other entity during the plurality of interactions. 3.The device of claim 2, wherein an amount of the modification of the atleast one neurostimulation programming parameter which changes the atleast one neurostimulation programming parameter from a first parameterstate to a second parameter state is correlated to an amount of changein the trust measurement value which changes the trust measurement valuefrom a first measurement state to a second measurement state.
 4. Thedevice of claim 2, wherein the plurality of interactions are performedwith text or voice conversations occurring between the human subject andthe other entity, and wherein the other entity creates the commitmentwith the human subject and performs at least one observable action tocause the fulfillment or the violation of the at least one commitment.5. The device of claim 2, wherein the trust measurement value isrepresentable as a value within a graph data structure, and wherein thegraph data structure provides a measurement of trust between the humansubject and the other entity, based on evaluation of the human subjectwith the plurality of interactions over a period of time.
 6. The deviceof claim 2, the data measurement processing circuitry further configuredto: identify a pain susceptibility value applicable to the humansubject, based on the trust measurement value derived from the at leastone commitment; wherein the pain susceptibility value is based on theprediction of the trust disposition for the human subject towards theother entity; and wherein the modification of at least oneneurostimulation programming parameter of the implantableneurostimulation device is further based on the pain susceptibilityvalue.
 7. The device of claim 6, wherein operations of the datameasurement processing circuitry to identify the pain susceptibilityvalue for the human subject are further based on an identification of apain measurement value derived from a neuroimaging procedure performedon the human subject; and wherein the identification of the painmeasurement value derived from the neuroimaging procedure is used todetermine a baseline to predict a placebo response to modification ofthe at least one neurostimulation programming parameter.
 8. The deviceof claim 1, wherein the results of the plurality of interactions includeresults determined from an observation of a reaction of the humansubject to a violation or fulfillment of the at least one commitment,and wherein the observation of the reaction is determined from theplurality of interactions with the human subject.
 9. The device of claim1, the data measurement processing circuitry further configured to:determine a subsequent trust measurement value, the subsequent trustmeasurement value being determined from a series of interactions whichoccur between the at least one entity and the human subject, the seriesof interactions being conducted after the modification of the at leastone neurostimulation programming parameter; determine a subsequentmodification of the at least one neurostimulation programming parameterof the implantable neurostimulation device, based on the subsequenttrust measurement value; and provide instructions to cause theimplantable neurostimulation device to implement the subsequentmodification of the at least one neurostimulation programming parameter.10. The device of claim 1, wherein the modification of the at least oneneurostimulation programming parameter is provided in a neurostimulationprogram for the implantable neurostimulation device, wherein theneurostimulation programming circuitry is further configured to: updatethe neurostimulation program based on the modification of the at leastone neurostimulation programming parameter; wherein the modification ofthe at least one neurostimulation programming parameter causes a changein programming for modulated energy provided with a plurality of leadsof the implantable neurostimulation device, the change in programmingspecified for one or more of: pulse patterns, pulse shapes, a spatiallocation of pulses, waveform shapes, or a spatial location of waveformshapes.
 11. A method for use to adjust programming of an implantableelectrical neurostimulation device for treating pain, the methodcomprising a plurality of operations executed with at least oneprocessor of an electronic device, the plurality of operationscomprising: identifying a trust measurement value, the trust measurementvalue being derived from results of a plurality of interactions havingpreviously occurred between at least one entity and a human subject, theplurality of interactions having caused at least one commitment to bemade between the at least one entity and the human subject, wherein thetrust measurement value is determined based on the at least onecommitment that is made between the at least one entity and the humansubject; determining a modification of at least one neurostimulationprogramming parameter of the implantable neurostimulation device, basedon the trust measurement value identified from the results of theplurality of interactions; and providing programming instructions to theimplantable neurostimulation device, the programming instructions tocause the implantable neurostimulation device to implement themodification of the at least one neurostimulation programming parameterand provide pain treatment to the human subject using the at least oneneurostimulation parameter.
 12. The method of claim 11, the operationsfurther comprising: determining the trust measurement value from areaction of the human subject to a fulfillment or a violation of the atleast one commitment; wherein the trust measurement value is determinedwith a classifier that performs analysis of the plurality ofinteractions for the fulfillment or the violation of the at least onecommitment, and wherein the classifier is trained to predict a trustdisposition for the human subject towards an other entity during theplurality of interactions.
 13. The method of claim 12, wherein an amountof the modification of the at least one neurostimulation programmingparameter which changes the at least one neurostimulation programmingparameter from a first parameter state to a second parameter state iscorrelated to an amount of change in the trust measurement value whichchanges the trust measurement value from a first measurement state to asecond measurement state.
 14. The method of claim 12, wherein theplurality of interactions are performed with text or voice conversationsoccurring between the human subject and the other entity, and whereinthe other entity creates the commitment with the human subject andperforms at least one observable action to cause the fulfillment or theviolation of the at least one commitment.
 15. The method of claim 12,wherein the trust measurement value is representable as a value within agraph data structure, and wherein the trust graph provides a measurementof trust between the human subject and the other entity, based onevaluation of the human subject with the plurality of interactions overa period of time.
 16. The method of claim 12, the operations furthercomprising: identifying a pain susceptibility value applicable to thehuman subject, based on the trust measurement value derived from the atleast one commitment; wherein the pain susceptibility value is based onthe prediction of the trust disposition for the human subject towardsthe other entity; and wherein the modification of at least oneneurostimulation programming parameter of the implantableneurostimulation device is further based on the pain susceptibilityvalue.
 17. The method of claim 16, wherein identifying the painsusceptibility value for the human subject is further based on anidentification of a pain measurement value derived from a neuroimagingprocedure performed on the human subject; and wherein the identificationof the pain measurement value derived from the neuroimaging procedure isused to determine a baseline to predict a placebo response tomodification of the at least one neurostimulation programming parameter.18. The method of claim 11, wherein the results of the plurality ofinteractions include results determined from an observation of areaction of the human subject to a violation or fulfillment of the atleast one commitment.
 19. The method of claim 11, the operations furthercomprising: identifying a subsequent trust measurement value, thesubsequent trust measurement value being identified from a series ofinteractions which occur between the at least one entity and the humansubject, the series of interactions being conducted after themodification of the at least one neurostimulation programming parameter;determining a subsequent modification of the at least oneneurostimulation programming parameter of the implantableneurostimulation device, based on the subsequent trust measurementvalue; and causing the implantable neurostimulation device to implementthe subsequent modification of the at least one neurostimulationprogramming parameter.
 20. The method of claim 11, wherein themodification of the at least one neurostimulation programming parameteris provided in a neurostimulation program for the implantableneurostimulation device, the operations further comprising: updating theneurostimulation program based on the modification of the at least oneneurostimulation programming parameter; wherein the modification of theat least one neurostimulation programming parameter causes a change inprogramming for modulated energy provided with a plurality of leads ofthe implantable neurostimulation device, the change in programmingspecified for one or more of: pulse patterns, pulse shapes, a spatiallocation of pulses, waveform shapes, or a spatial location of waveformshapes.